2024
NIPS
NeurIPS 2024
Learnability of high-dimensional targets by two-parameter models and gradient flow
Abstract
We explore the theoretical possibility of learning $d$-dimensional targets with $W$-parameter models by gradient flow (GF) when $W
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Cross-Pollinator
— Artificial Intelligence, Data Science & Analytics, Deep Learning, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning
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Interdisciplinary Bridge
— Deep Learning and Machine Learning
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Keyword Pioneer
— high-dimensional target